code: def _get_features(self, serialized_example):
      features = tf.parse_single_example(
          serialized_example,
          features={
              # images
              "image": tf.FixedLenFeature([], tf.string),
              "height": tf.FixedLenFeature([], tf.int64),
              "width": tf.FixedLenFeature([], tf.int64),
              # landmarks
              "n_landmarks": tf.FixedLenFeature([], tf.int64),
              "gt_pts": tf.FixedLenFeature([], tf.string),
              "gt_mask": tf.FixedLenFeature([], tf.string),
              "mask_index": tf.FixedLenFeature([], tf.string),
              "status": tf.FixedLenFeature([], tf.int64),
          },
      )
      return features
  
file_path: insightface/reconstruction/ostec/external/landmark_detector/data_provider.py
imports: import tensorflow
  import numpy
  from menpo.transform import Translation
  from external.landmark_detector.flags import FLAGS
label_desc: Use image node_id 8 for calling the ProtobuffProvider obj's underlying member method code with example usage: obj._get_features(serialized_example) and returns: features